There is very useful tool in QGIS that can import very large CSV files into PostgreSQL rapidly and reliably. The DB Manager’s “Import Vector Layer” tool. Contrary to its highly misleading title it can import CSV files as well. Open the DB Manager (menu Database – DB Manager). Then select the database where you want to store your table and click the “Import layer/file” icon.

From the Import Vector Layer GUI, locate our CSV file on disk and enter the name of your new table in the Table box and click OK. Yes, it’s that simple. Proceeding this, you may need to select an text encoding scheme, files created on Windows often use ISO-8859-1 (Latin-1) instead of UTF-8 encoding. In my case, I was able to import a large statistical data set describing the energy efficiency of 525,500 Irish homes (432 megabytes) into PostgreSQL in ~15 minutes. After the CSV file is imported, you can optionally add it to your project using the DB Manager, right-click the table and select Add to Canvas. Don’t use the “Add PostGIS Layers” menu, it’s not a PostGIS layer.

And one more useful tip. You can convert Tab delimited text to CSV using QGIS. Load a Tab delimited text file into QGIS using the Add Delimited Text Layer GUI, then right click the imported file in the layer panel and save it as a CSV file.

A very handy plugin for QGIS I use day to day is go2streetview by Enrico Ferreguti. The plugin adds an icon to the tool bar in QGIS and when selected I can click a road or street on a base map and a window will open that displays the Google Street or a Bing Maps Bird’s Eye view of the location. The camera’s direction and location is highlighted by a blue marker. I use the plugin when tracing boundaries of parks, open spaces and foot paths from aerial imagery. If the imagery is blurred or the view is obscured by trees, I click a point on a nearby street to see the location up close. The plugin works wherever Google Street view and Bing Birds Eye has coverage.

For example, in the screen-shot below notice there is a footpath leading to a bus shelter that’s not mapped by OpenStreetMap. I know where it is now, I will add it to my map.

CartoDB, the FOSS powered web mapping solution, was honoured at the 2014 European Web Entrepreneur of the Year Awards along with three other companies at Dublin’s Web Summit on November 7th. The awards, presented by a European Commission backed body, were announced after a six month competition that involved public voting across four categories. CartoDB won the award for best “high-growth web entrepreneur”. CartoDB now has a growth rate of over 15% per month and customers in over 30 countries.

In September, a partner company of CartoDB, Kudos Ltda., released a plug-in that allows QGIS users to view, create, edit and delete data stored on their CartoDB accounts. Here is a map I created with the help of the new CartoDB plug-in that shows mountains and hills across the contiguous United States in the form of a heat map.

CartoDB and QGIS illustrate the exciting convergence between web hosted and desktop GIS, where interactive maps created in QGIS can be quickly published on the web and viewed by a worldwide audience.

The 10th annual FOSS4G conference was held from 8th-13th September in Portland, Oregon, USA. FOSS4G is the world’s premier global gathering of developers, users and key decision-makers involved in open source geospatial software. With over 180 talks presented covering topics from 3D printing maps with Grass GIS 7 to QGIS Map Server and beyond, FOSS4G 2014 was a resounding success. Don’t be disappointed if you could not attend, all the talks given at FOSS4G 2014 are now viewable on Vimeo, including 8 one hour invited presentations from staff at Amazon, MapZen, Boundless, Mapbox etc. These talks are well worth watching if you want to keep up to date with the latest developments in open source geospatial software.

ESRI’s ArcGIS Online World Imagery is a high resolution satellite and aerial imagery base map for use in Google Earth, ArcMap and ArcGIS Explorer. The same excellent imagery is used by the Bing Maps Aerial layer. Somewhat surprisingly, World Imagery can also be accessed by QGIS, as it supports ESRI’s map servers that use Representational State Transfer (REST) and Simple Object Assess Protocol (SOAP) standards.

Simply copy and past the following code into the Python Console in QGIS and press return (Plugins – Console):

The code adds an ESRI Online World Imagery base map to QGIS. It has a number of advantages over the popular OpenLayers Plugin that adds various Google, Bing and OpenStreetMap image layers to QGIS. Unlike images downloaded by the OpenLayers plugin the ESRI World Imagery base map is a true Raster who’s attributes are fully editable e.g. brightness, blending mode and transparency can be adjusted. World Imagery can also be printed at a very high resolution with other QGIS layers on a map and without it shifting relative to other layers; a conspicuous problem with OpenLayers that does not use “On the Fly” re-projection and only prints Google, Bing layers at a low resolution. It is an ideal aerial base map.

Before the advent of shipborne satellite navigation systems, navigation at sea required three precise measurements – Solar or Stellar Declination for Latitude, Time at Greenwich for Longitude and True North that determined the ship’s heading. True North was obtained from the ship’s Magnetic Compass, an instrument who’s name indicates at an additional complication.

A magnetic compass does not point towards True North. Magnetic North is 100s km from the Geographic North Pole and the Earth’s magnetic field is uneven, it is distorted by magnetic irregularities within the Outer Core and intrinsically magnetic Mantle and Crustal rock. Additionally, the position of Magnetic North is not fixed, it is presently drifting from Arctic Canada towards Russia at 15 km per year. Therefore True North has to be derived from Magnetic North using a correction called Magnetic Declination (or Magnetic Variation), the angular difference between Magnetic North and True North. Magnetic Declination varies from location to location and over time.

Nautical navigation charts typically contain one or more Compass Roses, also called a Windrose, these consist of two circles – an outer circle that displays the cardinal directions of North, East, South and West and a inner circle that displays the direction of Magnetic North. The Magnetic Declination and its annual rate of change is typically printed within the Compass Rose, it is therefore possible to calculate the Magnetic Declination several years after a map is printed.

In this tutorial I will show you a process that to create a Compass Rose with the correct Magnetic Declination and Annual Rate of Change for any terrestrial location for use in QGIS. First we need to obtain a suitable Compass Rose graphic. Conveniently the United States National Oceanic and Atmospheric Administration (NOAA) published a Compass Rose in the Public Domain i.e. it is free to use without limitation. I downloaded a version of the NOAA Compass Rose from Wikimedia (or you can right click and save the Compass Rose below). Additionally, the background of this Compass Rose is transparent, this allows a map (or indeed a web page) to show though (note the Magnetic Declination in 1985 was 4 degrees 15 minutes west of True North and it had an annual decrease of 8 minutes of a degree per year).

There are several handy on-line utilities that can calculate Magnetic Declination and the Annual Rate of Change but we shall use Charles F. F. Karney’s excellent cross-platform GeographicLib in this case. GeographicLib is a suite of command line utilities for solving solving various geodesic problems such as conversions between geographic, UTM, UPS, MGRS, geocentric and local cartesian coordinates, gravity calculations, determining geoid height, and magnetic field calculations. The latest version can be obtained as a pre-compiled binary from Sourceforge or as source code.

The other essential step is to measure the precise map location in WGS84 coordinates. This can be done using the Coordinated Capture plug-in provided as standard with QGIS. To select the WGS84 coordinate reference system (CRS) click the sphere symbol in Coordinated Capture panel to open the Coordinate Reference System Selector. After setting the CRS to WGS84 (EPSG: 4326), click the icon left of the “Copy to Clipboard” button (this toggles real time display of captured coordinates) and then click “Start Capture”. The position in Decimal Degrees will be updated in the upper window as you move the cursor across the map, the lower window will display projected coordinates (in my case Pseudo Mercator EPSG: 3857). Clicking the map will select a coordinate point and the real time display will cease updating.

The MagneticField utility of GeographicLib is then used to calculate the Magnetic Declination and Annual Rate of Change for the captured coordinate, in this case a location east of Howth, Ireland.

The results are: Magnetic Declination in degrees (-3.57); the inclination of the Magnetic Field in degrees (67.81); the horizontal strength of the magnetic field in nanotesla (18572.9 nT); the north component of the field (18536.9 nT); the east component of the field in (-1152.2 nT); the vertical component of the field in nT (45528.7 nT) and the total field (49171.3 nT). The numbers on the second line are the annual rate of change of these values, the first number is. We only need the first numbers on each line; the Magnetic Declination (-3.57) and Annual Rate of Change of Magnetic Declination (0.17). We can convert these to Degrees Minutes Seconds if required.

After calculating the Magnetic Declination and Annual Rate of Change, edit the NOAA Compass Rose in a graphics program such as GIMP or Photoshop. In my case I copied the inner circle to a separate layer and I rotated it 3.57 degrees anticlockwise. I then added text to the Compass Rose stating the Magnetic Declination (Var.) and the Annual Rate of Change (Annual Decrease). After editing the Compass Rose graphic I finally added it to my Nautical Chart as a Image in Map Composer of QGIS.

Continuing with a nautical theme, here is a nautical chart I creating using QGIS 2.4. It includes a Graticule in decimal degrees, a Compass Rose and a scale bar in Nautical Miles. A magnetic declination of 3º 35′ was determined using the MagneticField utility of GeographicLib, an advanced software library for solving geodesic problems. I will post a full tutorial shortly.